Nonlinear Model Predictive Controller for the Real-Time control of Fast Dynamic System

Abstract

The computational complexity due to the system's non-linearity and non-convexity, restricts the use of nonlinear model predictive control (NMPC) for fast dynamic real time systems. This paper presents the real time development of the NMPC to control the highly nonlinear fast dynamic single rotary inverted pendulum (SRIP) system in inverted position with 20 millisecond sampling period which corresponds to nonlinear nonconvex optimization problem. This challenging problem is solved with online successive linearization and optimization on the compact reconfigurable input/output (cRIO) (field programmable gate array (FPGA)) hardware platform from National Instruments. The effectiveness of the control algorithm with the rapid disturbance rejection capability is validated using experimental results.